Chevron Left
返回到 Applied Social Network Analysis in Python

學生對 密歇根大学 提供的 Applied Social Network Analysis in Python 的評價和反饋

4.7
2,476 個評分
416 條評論

課程概述

This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem. This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....

熱門審閱

NK
2019年5月2日

This course is a excellent introduction to social network analysis. Learnt a lot about how social network works. Anyone learning Machine Learning and AI should definitely take this course. It's good.

JL
2018年9月23日

It was an easy introductory course that is well structured and well explained. Took me roughly a weekend and I thoroughly enjoyed it. Hope the professor follows up with more advanced material.

篩選依據:

126 - Applied Social Network Analysis in Python 的 150 個評論(共 406 個)

創建者 Rocco C

2017年10月9日

Very interesting course, thank you. The assignments could have been a bit more challenging.

創建者 Long T B

2020年10月27日

I really appreciate Coursera for offering this course. It is very valuable to my research.

創建者 Estella C

2020年7月30日

Very practical course! Explained all the concepts very clear and with meaning examples.

創建者 David T

2021年1月4日

I enjoyed the classes in this specialization. I felt that I have learned a great deal.

創建者 Parikshit A D

2020年5月3日

Best Course I have seen, learnt a lot about something to which I was completely new!!!

創建者 Мирзабекян А В

2018年8月9日

One of the most interesting and challenging courses in specialization, in my opinion.

創建者 Hiroki U

2020年11月30日

Assignment of week4 was tough, but interesting.

Thanks for making such a good course.

創建者 Reed R

2018年3月2日

Well taught and in a field which is not covered by many other data science curricula

創建者 Rajesh R

2018年2月7日

Excellent course to understand various networking principles and analyszng the same.

創建者 Carlos S

2017年10月8日

Great introduction to network theory and applications using Python Networkx library.

創建者 Krzysztof K

2020年11月5日

Very informative and useful content was presented in very easy to understand way.

創建者 Ricardo J M S

2020年6月1日

It is the best course of the 5 courses of the specialitation. I strongly recommend

創建者 Ferdinand C

2020年8月13日

Brilliant instructor! I really learned a great deal from this course. Thank you

創建者 Nicolás S

2021年1月3日

Nice topic to learn! Good materiales and tools were providade in thsi course

創建者 Vighneshbalaji

2020年4月28日

Very Useful. I learned a lot. Thanks to Coursera and University of Michigan

創建者 Chanaka S

2020年8月1日

Lecture is God To Me The Person Who has Good Knowledge then easy to study

創建者 Amila R

2019年9月30日

Good starting point for those who want ro learn social network analysis.

創建者 Roberto L L

2019年3月26日

It was a wonderful course, linked network's models and machine learning.

創建者 高宇

2018年12月2日

Very Nice Coursera! It lead me to reknow the relations among the worrld.

創建者 Thaweedet

2018年8月15日

Great, You will to learn how to develop feature for social network data

創建者 Mischa L

2018年1月6日

Great course. Very good homework assignments, but somewhat on easy side

創建者 Rui

2017年10月11日

very good introductory course for social network analysis using Python.

創建者 Diego F G L

2021年3月30日

Great course and and great contents. I really enjoyed the assignments.

創建者 Dirisala S

2019年7月22日

The have lot of stuff to learn. It will definitely enhance your skill.

創建者 Dibyendu C

2018年10月19日

Well structured and quality lecture content with excellent assignments